IBM SPSS Statistics is an integrated family of products that addresses the entire analytical process, from planning to data collection to analysis, reporting and deployment. With more than a dozen fully integrated modules to choose from, you can find the specialized capabilities you need to increase revenue, outperform competitors, conduct research and make better decisions.

SPSS Statistics is loaded with powerful analytic techniques and time-saving capabilities to help you quickly and easily find new insights in your data.

Here’s a look at the newest features and enhancements designed to help you:

Uncover hidden causal relationships among large numbers of time series using the Temporal Causal Modeling (TCM) technique. SPSS Statistics enables you to feed many time series into TCM to find out which series are causally related, and can automatically determine the best predictors for each target series.

SPSS Statistics includes geospatial analytics capabilities to help you explore the relationship between data elements that are tied to a geographic location.

In this map and graph, SPSS Statistics displays the point density (Kernel Density Estimation) of the selected regions over time.

Discover trends over time and space – Use the Spatio-Temporal Prediction (STP) technique to fit linear models for measurements taken over time at locations in 2D and 3D space, so you can predict how those areas may change over time.Create association rules that incorporate geospatial attributes – Find associations between spatial and non-spatial attributes using the Generalized Spatial Association Rule (GSAR). It uses historical data such as location, type of event and the time an event happened to describe the occurrences of events, such as crimes or disease outbreaks.

Develop and test R programs using a full-featured, integrated R development environment within SPSS Statistics. You can also write R functions that use SPSS Statistics functionality with command syntax from within R, and return results to R.